Why Customers Are Rejecting AI in Contact Centers and What Brands Can Do About It
Cx Today•2 months ago•
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Why Customers Are Rejecting AI in Contact Centers and What Brands Can Do About It

REMOTE JOBS | CUSTOMER SERVICE TIPS | COMPANIES | ARTICLES
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ai
contactcenter
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Summary:

  • 64% of customers prefer avoiding AI in customer service due to job loss, misinformation, and difficulty reaching live agents.

  • Investments in AI technologies like chatbots are set to grow despite customer skepticism.

  • The focus should shift from containment rates to outcome-driven metrics.

  • Companies must ensure a seamless escalation path to human support for effective customer service.

  • A strong data strategy is essential for delivering personalized customer experiences.

Customer Experience Crisis

The customer experience is at a crisis point, with contact centers nearing a breaking point. A recent Gartner report reveals that 64% of customers prefer companies to avoid using AI in customer service. Concerns include job loss, misinformation, and data security, but the primary worry is the difficulty in reaching a live person.

Shift to Customer Perspective

Steve Blood, VP of Market Intelligence at Five9, emphasizes the need to adopt an outside-in perspective—focusing on customer needs. Despite skepticism, investments in AI are expected to grow as companies aim to enhance customer experiences and agent efficiency.

Investment Trends in AI

Research from Five9 indicates that companies will continue to invest in AI technologies, particularly chatbots and intelligent virtual assistants (IVAs), to improve customer experiences. However, customers often perceive these tools as counterproductive.

Rethinking Success Metrics

The industry is often fixated on containment rates for self-service solutions, which may not reflect actual customer satisfaction. There’s a call for a shift towards outcome-driven metrics and ensuring customers have a clear path to escalate to human support when needed.

Seamless Escalation Paths

Blood advises against investing in AI solutions that lack a seamless escalation path to human agents. Companies should focus on high-volume transactions and gradually expand their chatbots’ capabilities while ensuring there is an easy transition to human support.

Data Strategy Importance

An effective data strategy is crucial for personalized customer experiences. If data is not accessible or usable, delivering capabilities becomes challenging. Blood highlights the importance of real-time, contextual data to respond effectively to customer needs.

For more insights, check out the video on Challenges & Opportunities: What Has 2024 Taught Us About AI in Contact Centers?.

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